Embodiments of the present invention relate to computerized systems of maintaining data with accuracy and, more particularly, to systems that provide accurate one-to-one conversions among various alternative units of measure.
As production processes get bigger and more standardized, many manufacturing and production plants handle their materials in “pieces” by developing a linked association between various variable types that are now necessarily consistent with each other. For example, a cable company may handle its materials in pieces, each piece having a predefined length and weight. Computer applications used by the company, such as product planning tools, typically define a level of precision for storing these various variables in its systems because the memory space is limited. Often, these values having different units of measure are used interchangeably, thereby requiring conversion among the values represented in different units of measure. Because of the predefined degree of precision, however, the conversion between different units of measure often leads to rounding errors.
For example, consider the same cable company that handles the cable in pieces. Assume further that the warehouse uses an inventory management system that allocates three decimal places for storing/displaying the weight of the cable pieces. Thus, in the inventory management system, one piece of cable weighs 2.333 KG/PC. If there are three pieces of cable pieces in the stock, the inventory management system may display 7.000 KG for the total weight of these cable pieces (conversion relation: 3 PCs=7 KG). If each piece was sold separately one piece after another, the inventory management system may display the following:
No. of Cable Pieces in StockTotal Weight (KG)37.00024.66712.33400.001As illustrated, when there is no cable piece left, the system may still indicate that the weight of cable is 0.001 KG. These rounding errors may seem nominal when the warehouse deals with a small quantity. But, if the warehouse is dealing with a large quantity, such as 30,000 pieces, the rounding error may be as big as 10 KG, which amounts to more than 4 pieces. Thus, as the production process gets bigger in scale, these inaccuracies in the conversions may cause unacceptable computational errors.
Moreover, the pieces used by these manufacturing and production systems are typically defined in more than one physical dimension. For example, in the above example, a piece of cable may be defined with three dimensions, its length, weight, and price. Each of these dimensional values represented in one unit of measure may also be represented in one or more alternative units of measure. For example, the length of cable may be represented in meters (M) or feet (FT). The weight of cable may also be represented in kilograms (KG) or pounds (LB). Further, the pieces of the cable may be priced in USD or Euro. These various values are correlated with one another, and each of these values in different units of measure is restricted to the same or similar degrees of precision. Such a system, however, may cause rounding errors when the value is converted to alternative units of measure of the same or different dimensions. Any attempt to perform product planning, for example, in the existence of these rounding errors, may result in inaccurate planning results.
The larger the difference in the degrees of precision between two variables the more significant the rounding errors will be. These rounding errors could lead to wasted resources, and sometimes, defects in the product production.
Accordingly, there is need in the art for a system that manages these quantities and provides an accurate one-to-one conversion among various values represented in alternative units of measures.